So sánh phương pháp

	Hồi quy Quantile	Hồi quy Lasso
Lĩnh vực	Kinh tế lượng	Học máy
Họ	Regression model	Machine learning
Năm ra đời	1978	1996
Người khởi xướng	Koenker & Bassett	Tibshirani, R.
Loại	Conditional quantile regression	Regularized linear regression (L1 penalty)
Công trình gốc	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society: Series B, 58(1), 267–288.
Tên gọi khác	conditional quantile regression, regression quantiles, Kantil Regresyon	LASSO Regresyonu, lasso, L1-regularized regression, L1 regularization
Liên quan	5	4
Tóm tắt	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.	Lasso regression, introduced by Robert Tibshirani in 1996, is a linear regression method that adds an L1 penalty to the loss so that it shrinks coefficients and performs variable selection at the same time, producing a sparse model. By driving some coefficients exactly to zero it keeps only the predictors that matter.